The CMF Muni Indices are based on the repeat sales regression (RSR) methodology. By observing sales of the same asset over time we can isolate market-wide trends that affect that asset’s price. We can then extrapolate those broader trends across groups of similar assets to estimate an index that represents a time series of price movements for assets, like municipal bonds, that trade infrequently.

We apply the RSR separately for each of the 50 largest cities (by population), 25 largest counties (by population) and ten largest school districts (by enrollment). For each jurisdiction we first identify all active general obligation (limited and unlimited) bonds where that jurisdiction is the obligor. We then compute the duration-adjusted yield-to-maturity on all secondary market trades in those bonds beginning on January 1, 2018. We drop all trades within the first month of a bond’s sale date and all trades within the final year to maturity. We then aggregate the remaining yields into a weekly index for each issuer using the RSR method. Each reported index weekly value is that jurisdiction’s inverted three-week moving average. There are enough secondary market trades to reliably construct the index for 32 of the 50 cities, 14 of the 25 counties, and five of the ten school districts.

Rising index values denote higher prices and, by implication, lower yields. Index values are best interpreted as percentages of the index values. For instance, if a jurisdiction’s index value was 120 in week one and 125 in week two, its week-on-week change is 4.2%. All indices are updated each Monday just after 9am ET. We also report an index value based on all trades in all bonds for the included jurisdictions. That index is depicted by the blue line in each figure.

Our application of the RSR method to munis is quite similar to Cornaggia, Hund and Nguyen’s (2022) paper “Investor Attention and Municipal Bond Returns“. Municipal Bond Information Services (MBIS) provides the CMF with the data for the indices. The uniquely comprehensive indices are able to be made using the robust historical trading data they possess. To share questions or feedback on the CMF Muni Indices, contact Justin Marlowe (jmarlowe@uchicago.edu).